A Monte Carlo-based electricity price risk prediction method and device

Abstract

The present invention provides a method and device for predicting electricity price risk based on Monte Carlo. The method includes: obtaining historical data of the electric power market; calculating and generating a historical data set of system remaining capacity ratio and a historical data set of congestion degree, and combining them in pairs Generate a two-dimensional point set of historical data; calculate and generate a random data set of system remaining capacity ratio and a random data set of congestion degree, and combine them to generate a two-dimensional point set of random data; calculate the electricity price mapping relationship, and according to the electricity price mapping relationship Calculate and form an electricity price level data set; calculate and obtain the electricity price risk level of the unprocessed node according to the electricity price level data set and a preset confidence level. The invention generates a random data set similar to a historical data set through a Monte Carlo method, and solves the problem of insufficient prediction accuracy caused by too few medium- and long-term electricity price prediction samples, thereby enabling accurate and comprehensive electricity price risk prediction.

Description

technical field [0001] The invention relates to the technical field of risk prediction, in particular to a Monte Carlo-based electricity price risk prediction method and device. Background technique [0002] With the gradual advancement of the historical reform of electricity, the price level of electricity is constantly changing due to the influence of various factors such as the relationship between market supply and demand, the market power of market players, and the cost of electricity production. In the market environment, accurate electricity price risk prediction is of great significance for market operators to implement market supervision and market entities to formulate trading strategies. [0003] At present, the commonly used electricity price risk quantification method is Value at Risk (VaR). This method accurately quantifies the electricity price risk by calculating the maximum possible loss of a product in a specific future period under a certain probability l...

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Problems solved by technology

[0004] In the early stage of electricity market construction, historical supply and demand data and clearing price data are often less than those in mature electricity markets. Traditional electricity price risk prediction based on Monte Carlo methods will cause large prediction deviations due to the small number of historical data samples.

How to reasonably expand the data sample based on the existing data set is a problem to be solved in the electricity price risk prediction through the Monte Carlo method. In addition, the traditional electricity price risk prediction method matching the influencing factors of the electricity price cannot fully reflect the changes in the key boundary conditions in the electricity market. , how to obtain a definite electricity price prediction result through reasonable mapping is also a key issue in electricity price risk prediction

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